I met with a company recently that started out on the clinical side doing fMRI brain imaging. They currently house the nations largest private dataset and have

I met with a company recently that started out on the clinical side doing fMRI brain imaging. They currently house the nations largest private dataset and have some very compelling sub-datasets in various areas, such as Parkinsons, ADHD, Alzheimers, and Strokes. They've hit the point of gaining enough training data and were moving onto the next phase where they wanted to utilize deep learning to help augment the doctors decision making. There's a ton of red tape here with the FDA but that was the near term goal. Augment the doctors decision making but not replace them. I believe they'll succeed in doing this one way or another. We had talked about also pairing brain imaging data with genetic data (eg. Alzheimers and mutations on APOE). The critical things we talked about were how we actually train the different models, what a sequential approach towards this type of software development would look like, etc. We believed that the most pertinent focus point would need to be a refined supervised deep learning model. I can definitely sympathize with the complexities of deep learning in healthcare.